- Stocks
AI may lead to market volatility
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Key points:
- AI is playing an increasingly important role in the financial sector, bringing both significant advantages and new risks.
- Artificial intelligence enables the processing of large amounts of data, leading to more accurate trading signals and better risk management.
- However, the rapid development of technology is outpacing the creation of effective regulatory mechanisms, which poses additional potential challenges.
The technological progress of recent decades has been a catalyst for the rapid development of financial markets. In particular, the widespread adoption of automated and algorithmic trading has led to a significant increase in the speed of trade execution, efficiency, and liquidity.
It is expected that artificial intelligence, with its powerful analytical capabilities, will further accelerate these positive transformations and have a revolutionary impact on financial markets. However, it is important to remember that any innovation comes with certain risks. In this case, there is a likelihood of increased short-term volatility and turbulence in financial markets.
The growing priority of AI for the market
Generative artificial intelligence technologies, represented by models like ChatGPT, are experiencing rapid adoption despite their relative newness. According to research by economists at the Federal Reserve Bank of St. Louis, the rate of adoption of generative AI in society has doubled the pace of the adoption of personal computers and the internet in the early years after their emergence. This trend is also supported by data on the frequency of AI mentions in corporate earnings reports, which has significantly increased since the launch of ChatGPT.
The financial industry isn’t lagging behind in this transformation. An analysis of patent applications shows that the share of applications related to algorithmic trading and incorporating AI elements has significantly increased in recent years, surpassing 50% in 2020. This suggests that financial markets are on the verge of a new wave of innovation driven by the development of generative AI.
The benefits of applying artificial intelligence in the financial sector are numerous. The ability of generative models to instantly analyze vast amounts of data allows for improved accuracy in trading signals, enhanced risk management, refined trading models, and the identification of new market trends.
Additionally, AI can help increase liquidity in financial markets and smooth out price distortions, particularly in segments with less liquid instruments, such as corporate bonds. As such, generative artificial intelligence presents the financial industry with vast opportunities to increase efficiency and optimize business processes.
Why might artificial intelligence be dangerous?
In its latest Global Financial Stability Report, the International Monetary Fund (IMF) highlighted several risks associated with the rapid development of artificial intelligence (AI) and its integration into financial markets. These conclusions are based on extensive consultations with market participants, including banks, brokers, AI developers, asset managers, and regulators.
One of the most pressing concerns is the potential reduction of liquidity or even the cessation of trading during periods of heightened volatility. AI-enhanced algorithmic trading strategies may trigger what is known as the “cascade effect,” amplifying market fluctuations and leading to undesirable outcomes. The risk of “herding behavior” is particularly high, where the majority of market participants act similarly, following signals generated by a limited number of AI models.
The IMF notes that such situations have already been observed in some markets, such as the U.S. stock market. During periods of increased stress, liquidity provided by algorithmic traders significantly decreased. This is because many algorithms were developed based on similar data and, therefore, react to market changes in a similar manner.
Moreover, the widespread adoption of AI may lead to the migration of trading activity to less regulated segments of the financial market, such as hedge funds and proprietary trading firms. The increased opacity of these segments will make it harder for regulators to monitor market activity and detect potential violations, such as cyberattacks, market manipulation, and the spread of misinformation.
Despite these risks, a return to the pre-AI era is no longer possible. Therefore, investors and regulators must be prepared for the new challenges posed by the development of artificial intelligence and take steps to mitigate the associated risks.
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